期刊文献+

对等网络应用中的网络统计特征分析 被引量:1

Network statistical analysis in peer-to-peer application
原文传递
导出
摘要 本文基于实测数据抽象出用户网络与资源网络,探讨了对等网络中用户、资源及其内部的相互作用关系,发掘并分析了其内在的网络统计特征.分析结果表明,用户节点度值及权值呈分段分布,体现了其各异的活跃性;网络资源的流行度差异明显,度值和权值近似呈幂律分布.用户网络与资源网络存在分簇结构,少数簇中含大量节点,多数簇所含节点数量较少.用户网络中,同簇内的用户有着相似的兴趣趋向,不同簇用户间兴趣趋向存在着差异,资源网络各簇中不同类别的资源间呈现出明显的关联性. The rich statistical characteristics in peer-to-peer(p2p) network have recently attracted much research interest.This paper reveals the internal network statistical characteristics in the user network and resource network,both of which are abstracted from the real application downloading logs.The two-segment degree and weight distribution of user nodes indicate the dynamic of p2p users,and the similar power-law distribution of resource nodes shows the popularity diversity.Furthermore,we found that these two networks have the inherent cluster structure,only minority of clusters contain a large number of nodes,and the majority have fewer nodes in it.In user network,users in the same cluster have similar filesharing interest,in contrast to the different user interest between clusters;meanwhile,there are obvious correlations between different resource categories in resource clusters.
出处 《物理学报》 SCIE EI CAS CSCD 北大核心 2011年第5期802-807,共6页 Acta Physica Sinica
基金 国家自然科学基金(批准号:60932005) 国家重点基础研究发展计划(批准号:2007CB307100 2007CB307105)资助的课题~~
关键词 对等网络 簇结构 网络统计特征 peer-to-peer network cluster structure network statistical characteristic
  • 相关文献

参考文献7

二级参考文献90

共引文献66

同被引文献18

  • 1Su Xiao-yuan, Taghi M K. A survey of collaborative filtering Techniques[J]. Advances in Artificial Intelligene, 2009, 9 :1-20.
  • 2Lieberman H. Letizia: An Agent That Assists Web Browsing [C]//Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence(IJCAI-95). San Mateo, CA: Morgan Kaufmann publishers Inc, 1995 : 924-929.
  • 3Michael J P, Jack M, Daniel B. Syskill&Webert: Identifying interesting Web sites[C]//Proceedings of the 13th National Conference on Articial Intelligence. Portland, OR, US, 1996 : 54-61.
  • 4Giles C L, Bollacker K D, Lawrence S. Citeseer: An automatic citation indexing system[C]//Proceeding of the 3rd ACM Conference on Digital Libraries. New York: ACM Press, 1998: 89-98.
  • 5Mobasher B, Cooley R, Jaideep S. Automatic personalization based on Web usage mining[J]. Communications of the ACM, 2000,43 (8) : 142-151.
  • 6Asnicar F, Tasso C. if Web:a prototype of user model-based intelligent agent for document filtering and navigation in the world wide Web[C]//Proceeding of the 6th International Conference on User Modelling. Chia Laguna, Sardinia, Italy, 1997 : 3-11.
  • 7David G, David N, Oki Brian M, et al. Using collaborative filtering to weave an information tapestry [J ]. Communication ACM, 1992,35(12) : 61-70.
  • 8Shardan U, Maes P. Social information filtering: Algorithms for automating "word of mouth"[C]//Proceedings of the SIGCHI conference on Human factors in computing systems. New York, USA, 1995 : 210-217.
  • 9Joseph A K, Bradley N M, David M, et al. Grouplens: applying collaborative filtering to usenet news[J]. Communications of the ACM, 1997,40(3) :77-87.
  • 10Loren T, Will H, Brian A, et al. Phoaks: A system for sharing recommendations[J]. Communications of the ACM, 1997, 40 (3) : 59-62.

引证文献1

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部